Train a Hotdog Image Recognition Model with Python
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Learn to train a hotdog image recognition model using Python. Understand the process of image classification and model training with real-world datasets for building accurate image classifiers.
At a Glance
We all know that machines can do a lot these days, including recognizing whether or not an image has a certain object in it. But did you know that you, too, can train a model to do just that? In this guided project, you’ll learn how to train a model in Python with PyTorch, a machine learning library, to detect if a picture has a hotdog in it. This process can be repeated with any object, whether it is a bird, a plane or even Superman!
A Look At the Project Ahead
- Create Python functions with libraries to preview, load and train your model to recognize hotdogs with PyTorch
- Transform a dataset of images to prepare it for training
- Train a state of the art image classifier by using transfer learning: training a model to solve one problem and applying that training to a related problem
What You’ll Need
- Basic Python knowledge
- Basic knowledge about image classification and neural networks, provided in optional readings
Instructor
Weiqing Wang, IBM
Other Contributors
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